DST Global is an investment firm that funds late-stage ventures in the internet industry. Its investments include some of the world’s fastest-growing and most valuable companies. DST Global has offices in Menlo Park, New York, London, Beijing, and Hong Kong. The firm was founded in 2009 by Yuri Milner, Saurabh Gupta, John Lindfors, Rahul Mehta, and Tom Stafford.

DST Global

Radical Ventures is an early-stage venture capital firm investing in entrepreneurs applying deep technology to transform massive industries. With a primary focus on artificial intelligence, Radical Ventures partners with entrepreneurs with global ambition to build enduring companies. The firm is based in Toronto, Canada, and is backed by global investors.

Radical Ventures

Snowflake Ventures invests in growth-stage companies that demonstrate a commitment to mobilizing data, providing value to its customers, and expanding opportunities for the data cloud.

Snowflake Ventures

Reka AI

Reka is an AI research and product company that develops models to benefit humanity, organizations, and enterprises. Reka, based in San Francisco, was founded by Dani Yogatama, Cyprien de Masson d'Autume, Qi Liu, Mikel Artetxe and Yi Tay.

<div>Reka is a developer of multimodal models and an AI assistant, founded by researchers from DeepMind, Google, and Meta in 2022. Reka's flagship application, Yasa-1, is a multimodal AI assistant based on its foundation model, Yasa. It is capable of understanding images, short videos, and audio snippets. In private preview (as of October 2023), Yasa-1 can be customized for various use cases using private datasets and supports 20 languages. Users can combine text-based prompts with multimedia to obtain more specific answers, such as generating social media posts from product images or identifying sounds, with context from the internet. Yasa-1 can even analyze videos, providing insights into discussed topics and predicting future actions. However, according to the company, the technology has some limitations, especially with intricate details in multimedia content and potential hallucinations, like other LLMs.</div>

Exploring the limitless possibilities of AI

Generative AI Applications

<div>Founded in 2022 by researchers from DeepMind, Google, and Meta, Reka develops multimodal models and an AI assistant. Reka's flagship application, Yasa-1, is a multimodal AI assistant based on its foundation model, Yasa. It is capable of understanding images, short videos, and audio snippets. In private preview (as of October 2023), Yasa-1 can be customized for various use cases using private datasets and supports 20 languages. Users can combine text-based prompts with multimedia to obtain more specific answers, such as generating social media posts from product images or identifying sounds, with context from the internet. However, according to the company, the technology has some limitations, especially with intricate details in multimedia content and potential hallucinations, like other LLMs.</div>

Foundation Models

Reka

<div>
 
 Reka is a developer of multimodal models and an AI assistant, founded by researchers from DeepMind, Google, and Meta in 2022. Reka's flagship application, Yasa-1, is a multimodal AI assistant based on its foundation model, Yasa. It is capable of understanding images, short videos, and audio snippets. In private preview (as of October 2023), Yasa-1 can be customized for various use cases using private datasets and supports 20 languages. Users can combine text-based prompts with multimedia to obtain more specific answers, such as generating social media posts from product images or identifying sounds, with context from the internet. Yasa-1 can even analyze videos, providing insights into discussed topics and predicting future actions. However, according to the company, the technology has some limitations, especially with intricate details in multimedia content and potential hallucinations, like other LLMs.
 
 
 Funding and financials
 
 
 In June 2023, Reka emerged from stealth raising USD 60 million in a funding round led by DST Global Partners and Radical Ventures to further develop the technology.
 
 
 
</div>

<div>
 
 Forethought offers a unified customer support platform based on generative AI. Its primary product is &ldquo;SupportGPT,&rdquo; a conversational AI chatbot that can build workflows, resolve queries, assist human agents, and fill knowledge gaps.&nbsp;
 
 
 Forethought&rsquo;s solutions include:
 
 
 1) Solve: A generative AI chatbot that independently handles simple but repetitive customer service tickets. The AI automatically analyzes historical customer service logs and knowledge documents to generate responses.&nbsp;
 
 
 2) Assist: Assists human agents by automatically generating responses to end users based on conversation history, provides context by analyzing past tickets, and draws on&nbsp; knowledge articles to help resolve queries.
 
 
 3) Triage: Analyzes ticket details and historical data to prioritize and route tickets to the correct agents
 
 
 4) Discover: Analyzes customer service history to generate new knowledge articles or recommend new workflows where gaps exist
 
 
 Forethought also offers a platform called &ldquo;SupportGPT Playground,&rdquo; which allows customers to train and experiment with SupportGPT using their own data. In September 2023, the company launched Autoflows that uses natural language prompts to undertake a series of tasks in order to automate customer service interactions.&nbsp;
 
 
 As of April 2023, Forethought&rsquo;s solutions were available for integration on several customer service platforms, including Zendesk, Salesforce, ServiceNow, Freshdesk, Dialpad, and Talkdesk.
 
 
 The platform leverages 
 <a href="https://sp-edge.com/companies/362567">
 OpenAI
 </a>
 &rsquo;s large language models (LLMs), using the same technology as ChatGPT, along with its own algorithms to limit the data that the AI model can access. This reduces the possibility of completely incorrect responses (hallucinations)&mdash;a documented issue with unconstrained LLMs such as ChatGPT. It does this by using the algorithms to generate a query that is submitted to the large AI model as a guide, which allows responses to be more specific to a customer&rsquo;s workflow.
 
 
 Key customers and partnerships
 
 
 At its launch in March 2023, its customers included Kickfin and Upwork. As of April 2023, Forethought&rsquo;s customers included Lime, iFIT, Achievers, Q4 Inc., Etekcity, Beeline, Uncommon Goods, Spoonflower, Kajabi, and PDQ.
 
 
 In October 2023, Forethought joined the 
 <a href="https://sp-edge.com/updates/23307">
 Amazon Web Services (AWS) 
 </a>
 Partner Network to make its services accessible on the AWS Marketplace.
 
 
 
 
 Funding and Financials
 
 
 In December 2021, Forethought raised USD 65 million in a Series C funding round led by Steadfast Capital to accelerate growth. Total raised funding stood at USD 92 million as of April 2023. In 2021, the company reported an increase in annual recurring revenue (ARR) by 5x.&nbsp;
 
 
 
</div>

Forethought

<div>
 
 Got It AI has developed a ChatGPT-like conversational chatbot for enterprise Q&amp;A applications. Its solutions include:
 
 
 1)&nbsp; ArticleBot: A virtual agent solution that analyzes an organization&rsquo;s customer service articles or external knowledge sources to provide accurate conversational support in customer service and employee workflow applications&nbsp;
 
 
 2) AutoFlows: A tool that helps analyze customer service voice, chat logs and other data to identify the dialogue paths in a given workflow and build them into a virtual agent. AutoFlows requires no code; integration with customer systems is assisted by a human team
 
 
 3) Truth Checker: An advanced AI that can identify if an AI is &ldquo;hallucinating,&rdquo; a common issue with large language models (LLMs) causing incorrect response generation. Truth Checker is able to detect when a response generated for a customer query is irrelevant or entirely incorrect, preventing the response from being delivered to the user and providing links to knowledge articles, if so.&nbsp;
 
 
 As of January 2023, ArticleBot operated on a fine-tuned version of Davinci-3, a variant of OpenAI&rsquo;s GPT-3.5 LLM, trained on a database defined by the organization alongside Got It&rsquo;s proprietary &ldquo;Truth Checker&rdquo; AI.&nbsp;
 
 
 For customers unwilling to use a large open-source LLM via an API or those that are unable to operate an expensive LLM on-premises, Got It offers its own proprietary Enterprise Language Model Architecture (ELMAR). Launched in March 2023, ELMAR is smaller than models like GPT-3 and can be run on readily available hardware. Combined with input scanning and Truth Checker AI, ELMAR is able to match larger models for accuracy in narrower enterprise workflows, such as customer Q&amp;A.
 
 
 Key customers and partnerships
 
 
 As of June 2022, Got It AI&rsquo;s customers included crowdfunding website Indiegogo and baby care product brand Frida.
 
 
 In October 2023, Got It AI partnered with 
 <a href="https://sp-edge.com/updates/22708">
 NVIDIA
 </a>
 AI Solutions to integrate its ELMAR platform with NVIDIA's AI technologies.
 
 
 Funding and financials
 
 
 Got It AI has raised a total of USD 22.5 million in funding as of April 2023 across several rounds and emerged from stealth in June 2022. Got It AI&rsquo;s co-founder and venture capitalist Peter Relan has participated in several of the firm&rsquo;s funding rounds.
 
 
 
</div>

Got It AI

<div>
 
 Persado is a &ldquo;motivation&rdquo; platform generating marketing content using machine learning. The platform recognizes different customers based on their reactions to language and uses those insights to generate personalized content that engages across all channels (web, email, ads, etc.) Persado&rsquo;s use cases include:
 
 
 1) Personalization: Identifying what content will motivate each customer to generate personalized messaging across all marketing channels
 
 
 2) Acquisition: Using personalized messaging for higher conversion rates in customer acquisition campaigns
 
 
 3) Onboarding: Personalizing content for each individual and engaging customers from the day of acquisition
 
 
 4) Retention: Keeping customers engaged using personalized messaging for renewals, loyalty programs, and upgrades
 
 
 5) Pre-collections: Promoting on-time payments using encouraging language and providing clear instructions&nbsp;
 
 
 6) Customer service: Encouraging customers to follow self-service prompts
 
 
 In August 2023, Persado launched 
 <a href="https://sp-edge.com/updates/21089">
 &ldquo;Essential Motivation&rdquo;,
 </a>
 to help marketers create emotionally resonant messages, to drive customer engagement and conversion rates. The company unveiled 
 <a href="https://sp-edge.com/updates/27700">
 new features
 </a>
 to this in March 2024, including new product descriptions, segment personalization, brand alignment scores, and web copy optimization, aimed at improving marketing content effectiveness.
 
 
 The Persado platform, based on a proprietary language model, uses a large consumer behavior database of historical interactions (1.2 billion consumers and over 100 billion interactions) to determine what qualities of a message appeal to consumers. Given a set of keywords as input, it leverages deep-learning transformer models to generate messages that are most likely to bring conversions, ensuring the content is in line with a customer&rsquo;s brand using specially trained language models.&nbsp;
 
 
 Over time, Persado uses machine-learning experimentation and decision-making to identify how messages cause each consumer to behave, enabling additional personalization for each future communication. The platform can also directly integrate with customer data platforms (CDPs) to leverage consumer language profiles.
 
 
 Persado also integrates with common marketing tools to fit into marketing teams&rsquo; workflows, providing detailed dashboards and analytics to visualize the impact of each piece of content.
 
 
 Key customers and partnerships
 
 
 Persado partnered with digital journey continuity platform Namogoo in May 2023, integrating its dynamic motivation platform with Namogoo&rsquo;s customer intent and segmentation database to allow ecommerce stores to dynamically adapt their messaging for individual customers.&nbsp;
 In March 2024, it partnered with 
 <a href="https://sp-edge.com/updates/27701">
 Bounteous x Accolite
 </a>
 to leverage Persado's language knowledge base and GenAI tools to enhance commerce and marketing experiences across diverse sectors.
 
 
 Persado&rsquo;s customers as of April 2023 include Vanguard Group, Marks &amp; Spencer, Chase Bank, Emirates NBD, and Vodafone.
 
 
 Funding and financials
 
 
 Persado raised USD 30 million in a Series C funding round held in April 2016 led by Goldman Sachs. The funds were for enhancing distribution and product development.&nbsp;
 
 
 
</div>

Persado

<div>
 
 Founded in 2022, SellScale is a GenAI-driven sales and marketing outbound platform that streamlines sales communication, which originated during the founders' work on the 
 <a href="https://www.dailydropout.fyi">
 DailyDropout.FYI
 </a>
 newsletter. This led to SellScale&rsquo;s evolution into a comprehensive solution, where sales development representatives (SDRs) utilize it to train GPT-3 and other language models using their top-performing outbound emails. It then customizes these emails using data from CRMs and 40+ data sources, including social media, RSS feeds, and articles. The platform optimizes sales workflows by prioritizing prospects, streamlining follow-ups, enabling multi-threaded engagement (generating leads from multiple contacts), and automating scheduling. It also integrates with tools like Gmail, Outreach.io, Apollo, LinkedIn, and Zapier to enhance workflow efficiency.
 
 
 
 
 The platform claims to improve revenue by 10x while reducing the time required to just 10%.
 
 
 
 
 Key customers and partnerships
 
 
 
 
 The firm's solutions are specialized for SDRs across healthcare, FinTech, technology, and business consulting, where the firm offers specialized targeting and playbooks for the respective industries by leveraging industry-specific data.
 
 
 
 
 Funding and financials
 
 
 In November 2022, the company raised USD 3.4 million in a seed funding round led by Pear Venture Capital.
 
 
 
</div>

SellScale

<div>
 
 DeckRobot is a platform compatible with Microsoft PowerPoint that leverages AI to transform raw slides into enterprise-ready presentations. DeckRobot AI transforms draft slides into professional, on-brand slides by adapting graphics from a vast library of slide examples. Users can apply an unlimited number of styles to any slide deck, including old documents, client materials, or web-sourced slides.&nbsp;
 
 
 
 
 DeckRobot offers enhancements for individual slides, such as adding approved icons and images, object alignment, slide resizing, and text validation through AI checks. DeckRobot's plugin acts as a time-saving tool for PowerPoint users, reducing manual work and potentially saving up to 80% of working time. The plugin emphasizes creating visually appealing presentations that adhere to company brand guidelines while maintaining content quality.&nbsp;
 
 
 
 
 Key customers and partnerships&nbsp;
 
 
 
 
 DeckRobot collaborates with clients from Fortune 500 companies and small businesses across over 50 countries.
 
 
 
</div>

DeckRobot

Generative AI applications are built on foundation models that are trained using advanced ML models

The technology allows the creation of digital avatars and virtual games

All companies within the space offer a product or service based on generative AI

The technology allows the creation of personalized content

Some applications leverage NLP to train models to process and respond to language-based prompts

Generative AI applications are built on in-house or third-party foundation models

Companies that offer natural language conversational chatbots providing answers for queries instead of links.

<div>
 
 Founded in 2022 by researchers from DeepMind, Google, and Meta, Reka develops multimodal models and an AI assistant. Reka's flagship application, Yasa-1, is a multimodal AI assistant based on its foundation model, Yasa. It is capable of understanding images, short videos, and audio snippets. In private preview (as of October 2023), Yasa-1 can be customized for various use cases using private datasets and supports 20 languages. Users can combine text-based prompts with multimedia to obtain more specific answers, such as generating social media posts from product images or identifying sounds, with context from the internet. However, according to the company, the technology has some limitations, especially with intricate details in multimedia content and potential hallucinations, like other LLMs.
 
 
 In February 2024, 
 <a href="https://sp-edge.com/updates/26584">
 Reka introduced a multimodal and multilingual language model, Reka Flash.
 </a>
 The new model includes 21 billion parameters and is trained on text from over 32 languages, claiming to outperform Llama 2, Grok-1, and GPT-3.5 in aspects such as reasoning, code generation, and question answering. The company also released a compact version of the model called &ldquo;Reka Edge,&rdquo; which has 7 billion parameters for scenarios with limited resources, mostly useful for on-device or local applications. Both models are available for beta testing.
 
 
 In April 2024, 
 <a href="https://sp-edge.com/updates/28508">
 the company introduced Core,
 </a>
 a frontier-class multimodal language model that is capable of understanding images, videos, and audio alongside textual data. The model has a large context window of 128K, can reason and generate code, and is trained in 32 languages.
 
 
 Key customers and partnerships
 
 
 In April 2024, 
 <a href="https://sp-edge.com/updates/28638">
 Reka partnered with Oracle Cloud Infrastructure
 </a>
 to enable Reka&rsquo;s multimodal models, supporting over 20 languages to be trained on Oracle for individuals and enterprises.
 
 
 Funding and financials
 
 
 In June 2023, Reka emerged from stealth raising USD 60 million in a funding round led by DST Global Partners and Radical Ventures to further develop its technology.
 
 
 
</div>

<div>
 
 AI21 is an Israel-based AI research lab developing large language models (LLMs). The firm also builds GenAI applications based on its LLMs, marketing them to businesses and consumers.&nbsp;
 
 
 AI21 launched its first AI model, &ldquo;Jurassic-1,&rdquo; in August 2021, offering two versions. The larger variant, Jurassic-1 Jumbo, contained 178 billion parameters&mdash;three billion more than OpenAI&rsquo;s 175-billion parameter GPT-3 model. Similar to GPT-3, Jurassic is able to write emails and articles, summarize text, compose poetry and recipes, create website layouts, and generate code.&nbsp;
 
 
 The firm concurrently launched AI21 Studio, a platform allowing users to train custom versions of Jurassic-1 and embed them into products via an API.&nbsp;
 
 
 In May 2022, AI21 confirmed it was working on a new AI system, called the &ldquo;modular reasoning knowledge and language&rdquo; or &ldquo;MRKL&rdquo; framework (pronounced &ldquo;miracle&rdquo;). MRKL augments LLMs, connecting to external sources and symbolic reasoning models to enable the generation of accurate historical information, news on current events, and dynamic information, such as weather, exchange rates, and Wikipedia information. This allows models to accurately answer math queries by calling a calculator and navigate more complex questions by breaking down queries into parts. An initial implementation of MRKL, Jurassic-X, is available on AI21 Studio, which allows users to connect LLMs to their own databases and navigate their data using natural language.
 
 
 In March 2023, the firm launched &ldquo;Jurassic-2,&rdquo; a successor to its initial language model. The new LLM differs from Jurassic-1 and most popular LLMs, in that it incorporates semantic reasoning into its text generation processes alongside statistical inference, enabling the model to more reliably and accurately respond to queries.
 
 
 AI21 says this was achieved by training Jurassic-2 in two phases: A traditional self-supervised phase using an extensive corpus of unstructured and unlabeled data and a second phase, involving a large volume of labeled data to teach the model to follow instructions. Jurassic-2 did not initially implement the MRKL framework, although AI21 confirmed it as an upcoming feature.
 
 
 
 
 The company claims that its foundation models are 30% more efficient than those of other providers and it also does not charge additional fees for the use of fine-tuned models.
 
 
 In March 2024,
 <a href="https://sp-edge.com/updates/27995">
 AI21 launched Jamba,
 </a>
 a model that integrates the Mamba Structured State Space model (SSM) technology and transformer components.
 
 
 Key customers and partnerships
 
 
 As of June 2023, AI21&rsquo;s customers include Latitude, Easyway, Verb, Tweet Hunter, and Harambee.
 
 
 Funding and financials
 
 
 In November 2023, 
 <a href="https://sp-edge.com/updates/24269">
 AI21 announced the closure of its
 </a>
 USD 208 million Series C financing round led by Intel Capital and Comcast Ventures alongside other undisclosed investors to promote its proprietary outlook of making AI purposes more specific, challenging the conventional &quot;one-size fits all&quot; approach.
 
 
 
</div>

AI21 Labs

<div>
 
 UK-based Stability AI is actively involved in building AI applications and offers a range of foundation models, including:
 
 
 Text-to-image model
 
 
 &bull; Stable Diffusion (SDXL 1.0): The open-source text-to-image model incorporates a dual network architecture with a 3.5-billion parameter base model and a 6.6-billion parameter refiner. The model was trained on image-caption pairs from the LAION-5B dataset derived from Common Crawl data. It excels in high-quality image generation, spatial object positioning, and complex concept recognition. The model can be fine-tuned for specific tasks using techniques such as embeddings, hypernetworks, and tools like DreamBooth, a deep-learning generation model.
 
 
 In November 2023, the company launched 
 <a href="https://sp-edge.com/updates/23352">
 two new products
 </a>
 Sky Replacer and Stable 3D. Sky Replacer lets users manipulate the aesthetic of the sky in their photos from a choice of nine alternatives, enhancing the overall image appeal and Stable 3D aims to simplify the process of creating textured 3D objects, from images or text prompts, into a quick, automatic activity.
 
 
 Text-to-text models
 
 
 1) Stable Beluga 1: The instruction-following language model is based on LLaMA 65 billion and has reasoning capabilities.
 
 
 2) Stable Beluga 2 (FreeWilly): An expansion to Stable Beluga 1, this model is based on LLaMA 70 billion and reportedly ranks near the top of the Open LLM Leaderboard.
 
 
 3) StableLM is an open-source language model suite; the company has released alpha versions of three billion- and seven-billion parameter models, with 15 to 65 billion-parameter models to follow. It's designed to generate text and code, and can power various downstream applications. 
 <a href="https://sp-edge.com/updates/25750">
 Stable LM 2 1.6B, 
 </a>
 an AI language model designed for multiple languages, was released in January 2024.
 
 
 4) The Japanese StableLM Alpha, is a seven-billion parameter Japanese language model, which claims to have superior performance compared to other publicly available Japanese language models. It offers text generation capabilities and is released under the Apache License 2.0 for commercial use, with an additional research version available for research purposes.
 
 
 5) StableCode has three billion parameters and is specifically designed to help programmers with coding tasks by providing autocomplete suggestions and responses to programming instructions.
 
 
 Text-to-audio model
 
 
 1) Stable Audio, which has 907 million parameters, uses a latent diffusion model architecture for audio and is conditioned on various factors including text metadata, audio file duration, and start time. This conditioning allows control over the content and length of the generated audio.
 
 
 Text-to-image model
 
 
 1) 
 <a href="https://sp-edge.com/updates/26910">
 Stable Diffusion 3,
 </a>
 which has 800 million range and 8 billion parameters and combines a diffusion transformer architecture and flow matching. Additionally, the model can depict multi-subject prompts, create images, and correct spelling.
 
 
 2) 
 <a href="https://sp-edge.com/updates/26645">
 Stable Cascade,
 </a>
 a text-to-image model developed with a three-phase approach for image creation and modification.
 
 
 Text-to-video model
 
 
 1) 
 <a href="https://sp-edge.com/updates/24289">
 Stable Video Diffusion
 </a>
 . an AI model designed to produce videos from images, offered as a research preview. The models, SVD and SVD-XT, can generate short, high-quality clips but come with limitations.
 
 
 2) 
 <a href="https://sp-edge.com/updates/27695">
 Stable Video 3D (SV3D), 
 </a>
 a GenAI tool to create 3D videos to create multi-view 3D models from a single input image and can produce short video content from image or text prompts.
 
 
 There has been considerable debate about the ethical and copyright implications of using stable diffusion to create images. The model is particularly permissive when it comes to creating different types of content, which has raised concerns about its potential for abuse. In response to its permissiveness, Stability AI has become involved in copyright infringement lawsuits, with artists and Getty Images raising legal objections to the use of their content in the model's training data.
 
 In March 2024, 
 <a href="https://sp-edge.com/updates/27872">
 Stability AI's founder and CEO, Emad Mostaque, resigned from his role 
 </a>
 and the company's board to focus on the development of decentralized AI to bring transparency and competitiveness in AI.&nbsp;
 
 
 In April 2024, the company made Stable Diffusion 3 and Stable Diffusion 3 Turbo available on the 
 <a href="https://sp-edge.com/updates/28612">
 Stability AI developer platform API.&nbsp;
 </a>
 
 
 Key customers and partnerships&nbsp;
 
 
 In December 2022, Stability AI entered a partnership with Amazon, with AWS designated as the preferred cloud provider to facilitate the development and expansion of Stability AI's AI models.
 
 
 In March 2024,
 <a href="https://sp-edge.com/updates/27403">
 Stability AI partnered with Tripo AI,
 </a>
 a provider of AI 3D models, to release TripoSR for 3D object reconstruction to cater to the demands of entertainment, gaming, industrial design, and architecture professionals, with responsive outputs for visualizing detailed 3D objects.&nbsp;
 
 
 In April 2024, the company
 <a href="https://sp-edge.com/updates/28612">
 partnered with Fireworks AI,
 </a>
 a provider of API platforms, to deliver Stable Diffusion 3 and Stable Diffusion 3 Turbo for enterprises.
 
 
 Funding and financials&nbsp;
 
 
 In October 2022, the company raised USD 101 million in a funding round led by Coatue and Lightspeed Venture Partners, bringing its post-money valuation to USD 1 billion. It planned to use the funds to scale custom versions of Stable Diffusion, boost supercomputing capabilities for AI model development, and expand its workforce from 100 to 300 employees in the coming year.
 
 
 <a href="https://sp-edge.com/updates/23765">
 In October 2023
 </a>
 , Stability AI reportedly raised a new round of financing from Intel, totaling approximately USD 50 million in the form of a convertible note to streamline product research with AI-driven solutions and is focused on further product releases in the coming months.
 
 
 
 
 
</div>

Stability AI

<div>
 
 Cohere is a Canadian startup founded in 2019 by Aidan Gomez, Ivan Zhang, and Nick Frosst, with backgrounds in natural language processing and prior experience at Google Brain. The firm specializes in the development and deployment of large language models (LLMs) for various applications across enterprise and business use cases. Its foundation model, Cohere Command, is a large natural language text generation model with 52.4 billion parameters, focused on task-oriented dialogue, creating summarization, copywriting, dialogue extraction, and question answering.&nbsp;
 
 
 Cohere also provides Cohere Embed, a model designed to generate vector embeddings that capture the essence of text, improving capabilities in search, content moderation, and intent recognition. These embeddings help empower Cohere's multilingual customizable models, which can be fine-tuned to cater to specific use cases and industries. Additionally, Cohere ensures secure deployment options, including private cloud solutions, for added data security and privacy. In November 2023, Cohere unveiled 
 <a href="https://sp-edge.com/updates/23446">
 Embed V3
 </a>
 with advanced capabilities in matching documents to queries, increasing the efficiency of retrieval augmented generation, and reducing the operational costs of LLM applications. In February 2024, the company introduced 
 <a href="https://sp-edge.com/updates/26583">
 Aya,
 </a>
 an open-source LLM that supports 101 languages.
 
 
 According to Stanford University's HELM benchmarks, Cohere's Command model ranks among the highest-performing models available.
 
 
 In March 2024,
 <a href="https://sp-edge.com/updates/27502">
 Cohere released an advanced language model, &ldquo;Command-R,
 </a>
 &rdquo; for enterprises. The model offers improved performance on retrieval augmented generation (RAG) and tool usage, with longer context windows of up to 128,000 tokens.
 
 
 In April 2024, 
 <a href="https://sp-edge.com/updates/28198">
 the company released an advanced language model, Command R+
 </a>
 , for business applications. The model offers enhanced retrieval augmented generation (RAG) with citation, supports 10 business languages, and automates workflows. Additionally, 
 <a href="https://sp-edge.com/updates/28463">
 Cohere also released Rerank 3,
 </a>
 a model designed to enhance enterprise search and RAG systems. In the same month, 
 <a href="https://sp-edge.com/updates/28509">
 the company also introduced a private beta for Cohere Compass,
 </a>
 a foundation embedding model designed to allow multi-aspect data indexing and searching, and also 
 <a href="https://sp-edge.com/updates/28789">
 launched a toolkit available for developers to build AI applications
 </a>
 faster, offering production-ready applications that can be deployed across cloud providers, with enhanced security and customization options.
 
 
 Key customers and partnerships&nbsp;
 
 
 In November 2021, Cohere partnered with Google Cloud to leverage its infrastructure support and TPUs for product development and deployment. Cohere also partnered with other major cloud providers like AWS and Oracle.&nbsp;
 
 
 In March 2024,
 <a href="https://sp-edge.com/updates/27307">
 Cohere partnered with consultancy firm Accenture
 </a>
 to integrate its Command model and retrieval augmented generation (RAG) capabilities to offer GenAI solutions for businesses.&nbsp;
 
 
 In April 2024, 
 <a href="https://sp-edge.com/updates/28932">
 Cohere partnered with Amazon 
 </a>
 to incorporate Command R+ and Command R to Amazon's cloud platform, Bedrock.
 
 
 Funding and financials&nbsp;
 
 
 In June 2023, the company raised USD 270 million in a Series C funding round led by Inovia Capital, bringing its post-money valuation to range between USD 2.1 billion&ndash;2.2 billion. It planned to use the funds to expand into &quot;search and retrieval&quot; to enable AI models to access real-time information from the web, improving its capabilities.
 
 
 
</div>

Cohere

<div>
 
 Founded in 2022, Hippocratic AI is a healthcare-focused AI model developed by Health GPT. At its core, Hippocratic AI uses a state-of-the-art (SOTA) large language model (LLM) designed to improve healthcare processes, particularly in non-diagnostic tasks. Hippocratic AI aims to differentiate itself from traditional LLMs by prioritizing pre-training with trusted, evidence-based healthcare content rather than the broader Internet. Claimed to be the first safety-focused LLM for healthcare, the model undergoes a unique Reinforcement Learning with Human Feedback process, known as RLHF-HP, which involves working with healthcare professionals to validate its readiness for use. In addition, the model aims to incorporate a compassionate &ldquo;bedside manner&rdquo; in its interactions with patients, recognizing the impact of empathy on emotional wellbeing and health outcomes.
 
 
 According to the company, Hippocratic AI outperformed GPT-4 in majority of tests and certifications. Out of 114 evaluations, it outperformed GPT-4 in 105 cases, with a notable margin of +5% in 74 evaluations and +10% in 43 certifications.
 
 
 Key customers and partnerships&nbsp;
 
 
 In August 2023, the company launched the Hippocratic AI Founding Partner Program, an initiative through which the company collaborates with leading healthcare organizations to become founding partners and actively participate in the development and validation of Hippocratic AI's LLM and technology. The program includes establishing use cases, ensuring clinical and patient safety, and contributing to the advancement of healthcare-specific AI applications. In February 2024, these companies began 
 <a href="https://sp-edge.com/updates/27145">
 beta
 </a>
 testing their LLM for non-diagnostic applications in healthcare.
 
 
 In March 2024, 
 <a href="https://sp-edge.com/updates/27696">
 Hippocratic AI partnered with NVIDIA
 </a>
 to develop AI healthcare agents that have low-latency conversational interactions with patients.
 
 
 Funding and financials&nbsp;
 
 
 In March 2024, 
 <a href="https://sp-edge.com/updates/27694">
 the company raised USD 53 million
 </a>
 in a Series A funding round co-led by Premji Invest and General Catalyst to invest in Phase III safety tests of its LLM and further develop of products.
 
 
 
</div>

Hippocratic AI

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 Founded in 2023, GenHealth.ai is a startup focused on advancing healthcare solutions through the use of GenAI. Its proprietary approach involves training a foundation transformer model, known as DOOG-E, on extensive healthcare data, including 50+ million of coded patient claims and clinical information. DOOG-E is a specialized Generative Pre-Trained Transformer (GPT) AI designed for healthcare applications, with 70 million parameters and one billion tokens. Unlike traditional large language models, DOOG-E is a large medical model (LMM) that uses medical events such as ICD, CPT, RxNorm, and LOINC codes as its &quot;language&quot; to predict future sequences of health events based on historical data.
 
 
 The company claims that its LMM, trained on medical data, is less prone to bias and hallucination compared to its GenAI, large language models (LLM), rendering it more dependable for healthcare applications.
 
 
 Funding and financials&nbsp;
 
 
 In July 2023, the company raised USD 13 million in early funding co-led by Craft Venture and Obvious Ventures. It planned to use the funds to support the development and expansion of its LMM for various healthcare applications, including risk adjustment, care management, and financial benchmarking.
 
 
 
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GenHealth

All companies within the space are building large AI models

Companies in this space leverage NLP to train LLMs

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All companies within the space can leverage their foundation models for generative AI applications

The technology enables the creation of personalized content

Foundation models that are trained to understand and work with two or more forms of input data (e.g., text and images) to solve problems and complete tasks using both natural language processing and computer vision. These models can also generate outputs across textual and visual modalities. Typical tasks include visual question answering, image captioning, and generating images based on text descriptions. These models typically use text and/or visual inputs and generate text and/or visual outputs.

Reka

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